使用智能手表早期检测阵发性心房颤动：验证研究

Use of a Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study.

作者信息

Inui Tomohiko, Kohno Hiroki, Kawasaki Yohei, Matsuura Kaoru, Ueda Hideki, Tamura Yusaku, Watanabe Michiko, Inage Yuichi, Yakita Yasunori, Wakabayashi Yutaka, Matsumiya Goro

机构信息

Department of Cardiovascular Surgery, University of Chiba, Chiba, Japan.

Clinical Research Center, University of Chiba, Chiba, Japan.

出版信息

JMIR Cardio. 2020 Jan 22;4(1):e14857. doi: 10.2196/14857.

DOI:10.2196/14857

PMID:32012044

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7003123/

Abstract

BACKGROUND

Wearable devices with photoplethysmography (PPG) technology can be useful for detecting paroxysmal atrial fibrillation (AF), which often goes uncaptured despite being a leading cause of stroke.

OBJECTIVE

This study is the first part of a 2-phase study that aimed at developing a method for immediate detection of paroxysmal AF using PPG-integrated wearable devices. In this study, the diagnostic performance of 2 major smart watches, Apple Watch Series 3 and Fitbit (FBT) Charge HR Wireless Activity Wristband, each equipped with a PPG sensor, was compared, and the pulse rate data outputted from those devices were analyzed for precision and accuracy in reference to the heart rate data from electrocardiography (ECG) during AF.

METHODS

A total of 40 subjects from patients who underwent cardiac surgery at a single center between September 2017 and March 2018 were monitored for postoperative AF using telemetric ECG and PPG devices. AF was diagnosed using a 12-lead ECG by qualified physicians. Each subject was given a pair of smart watches, Apple Watch and FBT, for simultaneous pulse rate monitoring. The heart rate of all subjects was also recorded on the telemetry system. Time series pulse rate trends and heart rate trends were created and analyzed for trend pattern similarities. Those trend data were then used to determine the accuracy of PPG-based pulse rate measurements in reference to ECG-based heart rate measurements during AF.

RESULTS

Of the 20 AF events in group FBT, 6 (30%) showed a moderate or higher correlation (cross-correlation function>0.40) between pulse rate trend patterns and heart rate trend patterns. Of the 16 AF events in group Apple Watch (workout [W] mode), 12 (75%) showed a moderate or higher correlation between the 2 trend patterns. Linear regression analyses also showed a significant correlation between the pulse rates and the heart rates during AF in the subjects with Apple Watch. This correlation was not observed with FBT. The regression formula for Apple Watch W mode and FBT was X=14.203 + 0.841Y and X=58.225 + 0.228Y, respectively (where X denotes the mean of all average pulse rates during AF and Y denotes the mean of all corresponding average heart rates during AF), and the coefficient of determination (R) was 0.685 and 0.057, respectively (P<.001 and .29, respectively).

CONCLUSIONS

In this validation study, the detection precision of AF and measurement accuracy during AF were both better with Apple Watch W mode than with FBT.

摘要

背景

采用光电容积脉搏波描记术（PPG）技术的可穿戴设备有助于检测阵发性心房颤动（AF），尽管其是中风的主要病因，但常常未被捕捉到。

目的

本研究是一项两阶段研究的第一部分，旨在开发一种使用集成PPG的可穿戴设备即时检测阵发性AF的方法。在本研究中，比较了两款主要智能手表（苹果手表Series 3和Fitbit（FBT）Charge HR无线活动腕带）的诊断性能，这两款手表均配备了PPG传感器，并参照AF期间心电图（ECG）的心率数据，分析了从这些设备输出的脉搏率数据的精度和准确性。

方法

对2017年9月至2018年3月在单一中心接受心脏手术的患者中的40名受试者，使用遥测ECG和PPG设备监测术后AF情况。由合格的医生使用12导联ECG诊断AF。给每位受试者一对智能手表（苹果手表和FBT），用于同时监测脉搏率。所有受试者的心率也记录在遥测系统上。创建并分析时间序列脉搏率趋势和心率趋势，以了解趋势模式的相似性。然后使用这些趋势数据，参照AF期间基于ECG的心率测量，确定基于PPG的脉搏率测量的准确性。

结果

在FBT组的20次AF事件中，6次（30%）的脉搏率趋势模式与心率趋势模式之间显示出中度或更高的相关性（互相关函数>0.40）。在苹果手表组（锻炼[W]模式）的16次AF事件中，12次（75%）的两种趋势模式之间显示出中度或更高的相关性。线性回归分析还显示，苹果手表组受试者在AF期间脉搏率与心率之间存在显著相关性。FBT组未观察到这种相关性。苹果手表W模式和FBT的回归公式分别为X = 14.203 + 0.841Y和X = 58.225 + 0.228Y（其中X表示AF期间所有平均脉搏率的平均值，Y表示AF期间所有相应平均心率的平均值），决定系数（R）分别为0.685和0.057（P值分别<0.001和0.29）。